AI-HCI: 4th International Conference on Artificial Intelligence in HCI

The conference aims to bring together academics, practitioners and students to exchange results from academic and industrial research, as well as industrial experiences, on the use of Artificial Intelligence technologies to enhance Human-Computer Interaction. In particular, the following areas of research are relevant: (i) Ethical and trustworthy AI to provide a fair and unbiased experience; (ii) Evolution of Human-Centered AI including models, processes and modalities; (iii) Processes, methods and technical frameworks in the area of generative UX / UI design, automatic creation and adaptation of user interfaces;  (iv) Consumer and industrial application domains including healthcare, finance, -market places, manufacturing and robots, (semi-) autonomous transportation, personal and industrial dashboards, personalized education and learning, and security.

The conference is targeted at individuals and organizations who have performed research or developed industrial applications in the area of AI in HCI. The conference is also targeted at individuals and organizations which want to learn from those results, so they can (re-)use them in research or industrial applications

Call for participation leaflet (161KB)

The AI in HCI Conference welcomes work with a strong user focus.
The related topics include, but are not limited to:

  • Ethical and trustworthy AI
    • Identifying and addressing biases and potential conflicts such as fairness, privacy, equity, diversity, sustainability, power assignment and distribution, norms, values / beliefs
    • Explainable AI, transparency, reliability, trust, and fairness
    • Metrics and KPIs
  • Human-Centered AI
    • Models: human modeling, social models, dialog / interaction models, technology models
    • Processes, tools, methods, standards, multi-disciplinary collaboration
    • Prototyping / simulation
    • User involvement, user research, evaluation, AI technology assessment and customization
    • Data acquisition strategy and  data quality
    • Interaction modalities and devices: visual, 2D / 3D, virtual and  augmented reality, simulations, digital twin, conversational interfaces, multimodal interfaces, brain-computer interfaces
  • Generative UX/UI design
    • Process: goal settings, model selection / training, data acquisition, learning and improvement, refinement.
    • Method and tools: users, data, interaction, domain, adaptability, evaluation
    • Generative UX/UI design frameworks
  • Consumer and industrial application domains
    • Healthcare & well-being: diagnostics support, treatment suggestions incl. explainability, evidence and confidence, e-healths, personalized healthcare, e-IoT, socially assistive robots
    • Cultural and art applications: Writing, painting, drawing, composing, arts, computer gaming
    • Financial applications: trends, predictions, bids, risk assessments, recommendations
    • Market places: match finding, trending, bidding, offering
    • Manufacturing & robots: human-robot teaming, human-robot interaction, safety
    • (Semi-) Autonomous transportation: monitoring and control, explainability, evidence and confidence, ethical conflict resolution, safety, social navigation
    • Personal and industrial dashboards: status, deviations, recommendations for preventive and corrective actions including explainability, evidence and confidence
    • Personalized education and e-learning: assessment, planning, content selection, progress measurements
    • Security: predicting and identifying vulnerabilities, predicting and suggesting mitigations, selecting and executing mitigations, monitoring incidents, penetration testing, digital forensics
  • Program Chair

    Helmut Degen

    Siemens Corporation, United States

  • Program Chair

    Stavroula Ntoa

    Foundation for Research & Technology - Hellas (FORTH), Greece

  • Board Members

  • Martin Boeckle
    BCG Platinion, Germany
  • Luis A. Castro
    Sonora Institute of Technology (ITSON), Mexico
  • Gennaro Costagliola
    Università di Salerno, Italy
  • Ahmad Esmaeili
    Purdue University, United States
  • Ozlem Ozmen Garibay
    University of Central Florida, United States
  • Mauricio Gomez
    University of Texas at San Antonio, United States
  • Julian Grigera
    LIFIA, Fac. de Informática, UNLP, Argentina
  • Thomas Herrmann
    Ruhr-University of Bochum, Germany
  • Pei-Hsuan Hsieh
    National Chengchi University, Taiwan
  • Sandeep Kaur Kuttal
    North Carolina State University, United States
  • Madhu Marur
    Currently on a break from work, Switzerland
  • Jennifer Moosbrugger
    Siemens, Germany
  • Adina Panchea
    Université de Sherbrooke, Canada
  • Ming Qian
    Charles River Analytics, United States
  • Robert G. Reynolds
    Wayne State University, United States
  • Anmol Srivastava
    University of Petroleum and Energy Studies (UPES), India
  • Brian C. Stanton
    National Institute of Standards and Technology (NIST), United States
  • Giuliana Vitiello
    University of Salerno, Italy
  • Brent Winslow
    Google, United States

Disclaimer - Political Neutrality

The HCI International Conference respects the decisions of all its contributors, engaged in any way, regarding their institutional affiliations and designations of territories, in all material / content published in its website, taking a neutral stance in relation to any disputes or claims. Moreover, the HCI International Conference fully concurs with the Territorial Neutrality Policy of Springer Nature, Publisher of its proceedings.